Quantitative methods have become increasingly important in the design and analysis of basic science, observational and randomized studies in cancer research, and health sciences research more generally. Modern biomedical research has become much more interdisciplinary. With the rapid advance of biotechnology and growing complexity of massive biomedical data, especially in genomics and proteomics, a significant number of challenging statistical and computational issues have emerged. Traditional statistical techniques cannot meet these new demands, leading to an increasing need to develop innovative statistical and computational methods to address these emerging issues in analyzing large and complex biomedical data sets. It would therefore be very valuable to have a platform in which biostatisticians and scientists can critique existing methods, present and discuss innovative new methods that have been developed, and identify priorities for future research. To respond to such a need, we propose a conference "Statistical Methods for Complex Biomedical Data", which would cover topics crucial to cancer research, and biomedical research in general, including nutritional epidemiology, measurement error models, nonparametric and semiparametric inference, functional data analysis, computational biology, and genetic epidemiology. This conference would provide quantitative and biomedical researchers a venue for stimulating interdisciplinary interaction. The Conference will be held at Texas A&M University in College Station, Texas, which houses a leading Statistics department. To increase its publicity and allow maximal attendance, it will be scheduled to take place just before the East North American Region meetings of the International Biometric Society which are in San Antonio, Texas in 2009. The specific aims are "To provide a timely and stimulating platform to engage biostatisticians, quantitative researchers, and biomedical scientists in cutting-edge in-depth discussions of emerging statistical and computational issues, especially in the areas of computational biology and genetic epidemiology, nutritional epidemiology, measurement error, nonparametric and semiparametric regression methods, and methods to analyze functional data. "To promote and foster interdisciplinary research and disseminate the discussions and the results to quantitative and subject-matter biomedical researchers, and engage junior investigators in these issues. Public Health Relevance: With the rapid advance of biotechnology and the increasing complexity of the data generated by biomedical studies, there are growing quantitative challenges that arise in cancer research, and biomedical research in general, that must be successfully addressed in order to make progress. Biostatistical researchers are working to address these challenges by developing and disseminating new statistical methodology that is needed in these fields. In this grant, we propose a conference "Statistical Methods for Complex Biomedical Data", in which we organize some of the top researchers in biostatistics to come together and present important cutting edge quantitative work in several key areas that are timely important for cancer research, and providing a platform for senior and junior investigators, quantitative and subject-matter biomedical researchers to engage in these issues.